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A machine readable multilingual dialog corpus.
Home-page: https://github.com/gunthercox/chatterbot-corpus Author: Gunther Cox Author-email: gunthercx@gmail.com License: BSD Download-URL: https://github.com/gunthercox/chatterbot-corpus/tarball/1.2.0 Description: ChatterBot Language Training Corpus ===================================
|Package Version| |Build Status|
These modules are used to quickly train ChatterBot to respond to various
inputs in different languages. Although much of ChatterBot is designed
to be language independent, it is still useful to have these training
sets available to prime a fresh database and make the variety of
responses that a bot can yield much more diverse.
For instructions on how to use these data sets, please refer to the
`project
documentation <http://chatterbot.readthedocs.io/en/latest/training.html#training-with-corpus-data>`__.
All training data contained within this corpus is user contributed.
If you are interested in contributing support for a new language please
create a pull request. Additions are welcomed!
Create your own Corpus Training data
====================================
Chatterbot is a very flexible and dynamic chatbot that you easily can
create your own training data and structure.
Create or copy an existing .yml file and put that file in a existing or
a new directory you created under
``chatterbot_corpus\data\<NEW DIRECTORY>`` Edit that file with any text
editor that you like to work with.
In the beginning of the file you set one or two categories.
::
categories:
- myown
- my own categories
Then can you start your actual training conversation data.
::
conversations:
- - Hello
- Hello
- - Hi
- Hello
Install your training corpus data to Django
===========================================
You need to install chatterbot as the `Quick Start
Guide <http://chatterbot.readthedocs.io/en/stable/quickstart.html>`__.
When the installation are done, please go to
``(Virtual Env)/lib/pythonX.X/site-packages/chatterbot_corpus/data/``
directory. Here is the same structure as you can find in this GitHub
repo, here is the area where you can create your own directories and
conversation files.
When you are done with your files, then can you edit the Django
``setting.py`` file and locate the chatterbot training section. Here do
you need to add ``chatterbot.corpus.<DIRECTORY>.<FILENAME>``
::
'training_data': [
'chatterbot.corpus.english.greeting',
'chatterbot.corpus.custom.myown',
'chatterbot.corpus.swedish.food'
]
When you are done, please proceed with the Django Chatterbot Training
session.
Unit Testing
============
“A true professional does not waste the time and money of other people
by handing over software that is not reasonably free of obvious bugs;
that has not undergone minimal unit testing; that does not meet the
specifications and requirements; that is gold-plated with unnecessary
features; or that looks like junk.” – Daniel Read
::
pip install -r requirements.txt
nosetests
.. |Package Version| image:: https://img.shields.io/pypi/v/chatterbot-corpus.svg
:target: https://pypi.python.org/pypi/chatterbot-corpus/
.. |Build Status| image:: https://travis-ci.org/gunthercox/chatterbot-corpus.svg?branch=master
:target: https://travis-ci.org/gunthercox/chatterbot-corpus
Keywords: chatterbot,dialog,language,corpus Platform: any Classifier: Development Status :: 4 - Beta Classifier: Intended Audience :: Developers Classifier: License :: OSI Approved :: BSD License Classifier: Environment :: Console Classifier: Environment :: Web Environment Classifier: Operating System :: OS Independent Classifier: Topic :: Software Development :: Libraries :: Python Modules Classifier: Topic :: Communications :: Chat Classifier: Topic :: Internet Classifier: Programming Language :: Python Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.4 Classifier: Programming Language :: Python :: 3.5 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: 3.7
FAQs
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We found that chatterbot-corpus demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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